Decision on the memory size of embedded information systems in an ubiquitous maintenance environment |
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| Authors: | Hong-Bae Jun Hyo-Won Suh |
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| Affiliation: | 1. Department of Industrial and Information Engineering, Hongik University, 72-1 Sangsu-dong, Mapo-gu, Seoul 121-791, Republic of Korea;2. Department of Industrial Engineering, KAIST, Daejon, Republic of Korea;1. Dipartimento di Scienze Economiche, Aziendali, Matematiche e Statistiche, Università di Trieste, Piazzale Europa 1, 34127, Trieste, Italy;2. Dipartimento di Economia e Management, Università degli Studi di Brescia, Contrada Santa Chiara 50, 25122 Brescia, Italy;1. Department of Mathematics, Linköping University, 581 83 Linköping, Sweden;2. Middlesex College, University of Western Ontario, London, Ontario, N6A 5B7, Canada;1. School of Mathematics, University of the Witwatersrand, 2050 Johannesburg, South Africa;2. Department of Mathematical Sciences, Binghamton University, Binghamton, NY 13902-6000, United States;1. Department of Physics, Liaoning Normal University, Dalian 116029, China;2. Department of Physics and State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing 100871, China;3. Department of Physics and Astronomy, Louisiana State University, Baton Rouge, LA 70803-4001, USA;4. Center for High Energy Physics, Peking University, Beijing 100871, China;5. Department of Physics, Shanghai Jiao Tong University, Shanghai 200240, China;6. Department of Physics and Astronomy, University of Tennessee, Knoxville, TN 37996, USA |
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| Abstract: | Over the last decade, emerging information communication technologies have changed our stereotype of manufacturing and service companies. Now products equipped with embedded systems can be wirelessly networked, which leads to gathering and analyzing product status, and taking appropriate actions for maintenance operations during product lifecycle in an ubiquitous way. In this environment, it is necessary to determine the appropriate memory size of embedded systems for minimizing total maintenance system costs because the memory cost is a main cost factor for implementing the ubiquitous maintenance environment. We call it memory size decision problem in this study. We have formulated this problem with a non-linear model having constraints. The decision variable is the memory size of each embedded system. To solve this problem, we have proposed a meta heuristic search method based on genetic algorithms. To show the usefulness of the proposed heuristic, we have carried out computational experiments. |
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